Bias (Galaxy Bias)

Bias Theory

class soliket.bias.Bias(info: Mapping[str, Any] = mappingproxy({}), name: str | None = None, timing: bool | None = None, packages_path: str | None = None, initialize=True, standalone=True)

Parent class for bias models.

get_requirements() → dict[str, Any]

Get a dictionary of requirements (or a list of requirement name, option tuples) that are always needed (e.g. must be calculated by another component or provided as input parameters).

Returns:

dictionary or list of tuples of requirement names and options (or iterable of requirement names if no optional parameters are needed)

initialize()

Initializes the class (called from __init__, before other initializations).

must_provide(**requirements) → dict[str, Any]

Function called by Cobaya with the actual products that this component needs to compute (i.e. the things this component can provide that are actually used by other components). The function can return conditional requirements that this component needs from other components in order to compute those things.

The requirements argument is a requirement name with any optional parameters. This function may be called more than once with different requirements.

Returns:

optional dictionary (or list of requirement name, option tuples) of conditional requirements for the ones requested.

Linear Bias

class soliket.bias.Linear_bias(info: Mapping[str, Any] = mappingproxy({}), name: str | None = None, timing: bool | None = None, packages_path: str | None = None, initialize=True, standalone=True)

Synopsis:

Linear bias model.

Has one free parameter, \(b_\mathrm{lin}\) (b_lin).

calculate(state: dict, want_derived: bool = True, **params_values_dict)

Do the actual calculation and store results in state dict

Parameters:

• state – dictionary to store results

• want_derived – whether to set state[‘derived’] derived parameters

• params_values_dict – parameter values

Returns:

None or True if success, False for fail